Laravel AI SDK

ANTHROPIC_API_KEY=
AZURE_OPENAI_API_KEY=
COHERE_API_KEY=
DEEPSEEK_API_KEY=
ELEVENLABS_API_KEY=
GEMINI_API_KEY=
GROQ_API_KEY=
MISTRAL_API_KEY=
OLLAMA_API_KEY=
OPENAI_API_KEY=
OPENROUTER_API_KEY=
JINA_API_KEY=
VOYAGEAI_API_KEY=
XAI_API_KEY=

'providers' => [
    'openai' => [
        'driver' => 'openai',
        'key' => env('OPENAI_API_KEY'),
        'url' => env('OPENAI_URL'),
    ],
    'anthropic' => [
        'driver' => 'anthropic',
        'key' => env('ANTHROPIC_API_KEY'),
        'url' => env('ANTHROPIC_BASE_URL'),
    ],
],

'providers' => [
    'local' => [
        'driver' => 'openai-compatible',
        'url' => env('LOCAL_AI_URL'),
        'key' => env('LOCAL_AI_API_KEY'),
    ],
],

agent()->prompt('What is Laravel?', provider: 'local', model: 'local-model');

'local' => [
    'driver' => 'openai-compatible',
    'url' => env('LOCAL_AI_URL'),
    'key' => env('LOCAL_AI_API_KEY'),
    'models' => [
        'text' => [
            'default' => env('LOCAL_AI_MODEL'),
        ],
    ],
],

use Laravel\Ai\Enums\Lab;

Lab::Anthropic;
Lab::OpenAI;
Lab::Gemini;

php artisan make:agent SalesCoach

# 生成带结构化输出的智能体
php artisan make:agent SalesCoach --structured

<?php

namespace App\Ai\Agents;

use App\Ai\Tools\RetrievePreviousTranscripts;
use App\Models\History;
use App\Models\User;
use Illuminate\Contracts\JsonSchema\JsonSchema;
use Laravel\Ai\Contracts\Agent;
use Laravel\Ai\Contracts\Conversational;
use Laravel\Ai\Contracts\HasStructuredOutput;
use Laravel\Ai\Contracts\HasTools;
use Laravel\Ai\Messages\Message;
use Laravel\Ai\Promptable;
use Stringable;

class SalesCoach implements Agent, Conversational, HasTools, HasStructuredOutput
{
    use Promptable;

    public function __construct(public User $user) {}

    public function instructions(): Stringable|string
    {
        return 'You are a sales coach, analyzing transcripts and providing feedback and an overall sales strength score.';
    }

    public function messages(): iterable
    {
        return History::where('user_id', $this->user->id)
            ->latest()
            ->limit(50)
            ->get()
            ->reverse()
            ->map(function ($message) {
                return new Message($message->role, $message->content);
            })->all();
    }

    public function tools(): iterable
    {
        return [new RetrievePreviousTranscripts];
    }

    public function schema(JsonSchema $schema): array
    {
        return [
            'feedback' => $schema->string()->required(),
            'score' => $schema->integer()->min(1)->max(10)->required(),
        ];
    }
}

$response = (new SalesCoach)->prompt('Analyze this sales transcript...');
return (string) $response;

$agent = SalesCoach::make(user: $user);

$response = (new SalesCoach)->prompt(
    'Analyze this sales transcript...',
    provider: Lab::Anthropic,
    model: 'claude-haiku-4-5-20251001',
    timeout: 120,
);

use Laravel\Ai\Concerns\RemembersConversations;

class SalesCoach implements Agent, Conversational
{
    use Promptable, RemembersConversations;

    public function instructions(): string
    {
        return 'You are a sales coach...';
    }
}

$response = (new SalesCoach)->forUser($user)->prompt('Hello!');
$conversationId = $response->conversationId;

$response = (new SalesCoach)->continue($conversationId, as: $user)->prompt('Tell me more about that.');

public function schema(JsonSchema $schema): array
{
    return ['score' => $schema->integer()->required()];
}

$response = (new SalesCoach)->prompt('Analyze this...');
return $response['score'];

public function schema(JsonSchema $schema): array
{
    return [
        'score' => $schema->integer()->required(),
        'metadata' => $schema->object(fn ($schema) => [
            'confidence' => $schema->string()->enum(['low', 'medium', 'high'])->required(),
            'language' => $schema->string()->required(),
        ])->required(),
    ];
}

public function schema(JsonSchema $schema): array
{
    return [
        'feedback' => $schema->array()->items(
            $schema->object(fn ($schema) => [
                'comment' => $schema->string()->required(),
                'score' => $schema->integer()->required(),
            ])
        )->required(),
    ];
}

public function schema(JsonSchema $schema): array
{
    return [
        'content' => $schema->anyOf([
            $schema->object(fn ($schema) => [
                'type' => $schema->string()->enum(['article'])->required(),
                'title' => $schema->string()->required(),
            ]),
            $schema->object(fn ($schema) => [
                'type' => $schema->string()->enum(['image'])->required(),
                'url' => $schema->string()->required(),
            ]),
        ])->required(),
    ];
}

use Laravel\Ai\Files;

$response = (new SalesCoach)->prompt(
    'Analyze the attached sales transcript...',
    attachments: [
        Files\Document::fromStorage('transcript.pdf'),
        Files\Document::fromPath('/home/laravel/transcript.md'),
        $request->file('transcript'),
    ]
);

$response = (new ImageAnalyzer)->prompt('What is in this image?', attachments: [
    Files\Image::fromStorage('photo.jpg'),
    Files\Image::fromPath('/home/laravel/photo.jpg'),
    $request->file('photo'),
]);

Route::get('/coach', function () {
    return (new SalesCoach)->stream('Analyze this sales transcript...');
});

use Laravel\Ai\Responses\StreamedAgentResponse;

Route::get('/coach', function () {
    return (new SalesCoach)
        ->stream('Analyze this sales transcript...')
        ->then(function (StreamedAgentResponse $response) {
            // $response->text, $response->events, $response->usage...
        });
});

$stream = (new SalesCoach)->stream('Analyze this sales transcript...');

foreach ($stream as $event) {
    // ...
}

Route::get('/coach', function () {
    return (new SalesCoach)->stream('Analyze...')->usingVercelDataProtocol();
});

use Illuminate\Broadcasting\Channel;

$stream = (new SalesCoach)->stream('Analyze this sales transcript...');

foreach ($stream as $event) {
    $event->broadcast(new Channel('channel-name'));
}

(new SalesCoach)->broadcastOnQueue(
    'Analyze this sales transcript...',
    new Channel('channel-name'),
);

<?php

namespace App\Ai\Agents;

use Laravel\Ai\Attributes\WithoutBroadcasting;
use Laravel\Ai\Contracts\Agent;
use Laravel\Ai\Contracts\HasTools;
use Laravel\Ai\Promptable;
use Laravel\Ai\Streaming\Events\ToolCall;
use Laravel\Ai\Streaming\Events\ToolResult;

#[WithoutBroadcasting(ToolCall::class, ToolResult::class)]
class SearchAgent implements Agent, HasTools
{
    use Promptable;

    // ...
}

use Laravel\Ai\Responses\AgentResponse;

Route::post('/coach', function (Request $request) {
    (new SalesCoach)
        ->queue($request->input('transcript'))
        ->then(function (AgentResponse $response) { /* ... */ })
        ->catch(function (Throwable $e) { /* ... */ });

    return back();
});

php artisan make:tool RandomNumberGenerator

<?php

namespace App\Ai\Tools;

use Illuminate\Contracts\JsonSchema\JsonSchema;
use Laravel\Ai\Contracts\Tool;
use Laravel\Ai\Tools\Request;
use Stringable;

class RandomNumberGenerator implements Tool
{
    public function description(): Stringable|string
    {
        return 'This tool may be used to generate cryptographically secure random numbers.';
    }

    public function handle(Request $request): Stringable|string
    {
        return (string) random_int($request['min'], $request['max']);
    }

    public function schema(JsonSchema $schema): array
    {
        return [
            'min' => $schema->integer()->min(0)->required(),
            'max' => $schema->integer()->required(),
        ];
    }
}

public function tools(): iterable
{
    return [new RandomNumberGenerator];
}

use App\Models\Document;
use Laravel\Ai\Tools\SimilaritySearch;

public function tools(): iterable
{
    return [
        SimilaritySearch::usingModel(Document::class, 'embedding'),
    ];
}

SimilaritySearch::usingModel(
    model: Document::class,
    column: 'embedding',
    minSimilarity: 0.7,
    limit: 10,
    query: fn ($query) => $query->where('published', true),
),

new SimilaritySearch(using: function (string $query) {
    return Document::query()
        ->where('user_id', $this->user->id)
        ->whereVectorSimilarTo('embedding', $query)
        ->limit(10)
        ->get();
}),

SimilaritySearch::usingModel(Document::class, 'embedding')
    ->withDescription('Search the knowledge base for relevant articles.'),

use Laravel\Ai\Tools\FileStorage;

public function tools(): iterable
{
    return FileStorage::all('local');
}

return FileStorage::readOnly('local');

use Laravel\Ai\Tools\Filesystem\DeleteFile;

return FileStorage::all('s3')
    ->reject(fn ($tool) => $tool instanceof DeleteFile);

use App\Ai\Tools\RandomNumberGenerator;
use Laravel\Mcp\Client;

/**
 * Get the tools available to the agent.
 *
 * @return Tool[]
 */
public function tools(): iterable
{
    return [
        ...Client::web('https://mcp.example.com')
            ->withToken($token)
            ->tools(),

        new RandomNumberGenerator,
    ];
}

use Laravel\Mcp\Facades\Mcp;

public function tools(): iterable
{
    return [
        ...Mcp::client('github')->tools(),
    ];
}

use Laravel\Mcp\Client;

public function tools(): iterable
{
    return [
        ...Client::local('php', ['artisan', 'mcp:start'])->tools(),
    ];
}

use Laravel\Ai\Providers\Tools\WebSearch;

public function tools(): iterable
{
    return [new WebSearch];
}

(new WebSearch)->max(5)->allow(['laravel.com', 'php.net']),
(new WebSearch)->location(city: 'New York', region: 'NY', country: 'US');

use Laravel\Ai\Providers\Tools\WebFetch;

public function tools(): iterable
{
    return [new WebFetch];
}

(new WebFetch)->max(3)->allow(['docs.laravel.com']),

use Laravel\Ai\Providers\Tools\FileSearch;

public function tools(): iterable
{
    return [new FileSearch(stores: ['store_id'])];
}

// 指定多个向量库
new FileSearch(stores: ['store_1', 'store_2']);

// 按元数据过滤
new FileSearch(stores: ['store_id'], where: ['author' => 'Taylor Otwell', 'year' => 2026]);

use Laravel\Ai\Providers\Tools\FileSearchQuery;

new FileSearch(stores: ['store_id'], where: fn (FileSearchQuery $query) =>
    $query->where('author', 'Taylor Otwell')
          ->whereNot('status', 'draft')
          ->whereIn('category', ['news', 'updates'])
);

<?php

namespace App\Ai\Agents;

use Laravel\Ai\Contracts\Agent;
use Laravel\Ai\Contracts\HasTools;
use Laravel\Ai\Promptable;

class CustomerSupportAgent implements Agent, HasTools
{
    use Promptable;

    public function instructions(): string
    {
        return 'You help customers with account, order, and billing questions. Delegate refund policy questions to the refunds specialist.';
    }

    public function tools(): iterable
    {
        return [
            new RefundsAgent,
        ];
    }
}

<?php

namespace App\Ai\Agents;

use App\Ai\Tools\LookupOrder;
use Laravel\Ai\Attributes\Provider;
use Laravel\Ai\Contracts\Agent;
use Laravel\Ai\Contracts\CanActAsTool;
use Laravel\Ai\Contracts\HasTools;
use Laravel\Ai\Enums\Lab;
use Laravel\Ai\Promptable;

#[Provider(Lab::Anthropic)]
class RefundsAgent implements Agent, CanActAsTool, HasTools
{
    use Promptable;

    public function instructions(): string
    {
        return 'You are a refunds specialist. Use order details and the refund policy to give concise eligibility guidance.';
    }

    public function name(): string
    {
        return 'refunds_specialist';
    }

    public function description(): string
    {
        return 'Determine whether an order is eligible for a refund and explain the next step.';
    }

    public function tools(): iterable
    {
        return [
            new LookupOrder,
        ];
    }
}

php artisan make:agent-middleware LogPrompts

<?php

namespace App\Ai\Agents;

use App\Ai\Middleware\LogPrompts;
use Laravel\Ai\Contracts\Agent;
use Laravel\Ai\Contracts\HasMiddleware;
use Laravel\Ai\Promptable;

class SalesCoach implements Agent, HasMiddleware
{
    use Promptable;

    public function middleware(): array
    {
        return [new LogPrompts];
    }
}

<?php

namespace App\Ai\Middleware;

use Closure;
use Laravel\Ai\Prompts\AgentPrompt;

class LogPrompts
{
    public function handle(AgentPrompt $prompt, Closure $next)
    {
        Log::info('Prompting agent', ['prompt' => $prompt->prompt]);
        return $next($prompt);
    }
}

public function handle(AgentPrompt $prompt, Closure $next)
{
    return $next($prompt)->then(function (AgentResponse $response) {
        Log::info('Agent responded', ['text' => $response->text]);
    });
}

use function Laravel\Ai\{agent};

$response = agent(
    instructions: 'You are an expert at software development.',
    messages: [],
    tools: [],
)->prompt('Tell me about Laravel');

use Illuminate\Contracts\JsonSchema\JsonSchema;

$response = agent(
    schema: fn (JsonSchema $schema) => ['number' => $schema->integer()->required()],
)->prompt('Generate a random number less than 100');

<?php

namespace App\Ai\Agents;

use Laravel\Ai\Attributes\MaxSteps;
use Laravel\Ai\Attributes\MaxTokens;
use Laravel\Ai\Attributes\Model;
use Laravel\Ai\Attributes\Provider;
use Laravel\Ai\Attributes\Temperature;
use Laravel\Ai\Attributes\Timeout;
use Laravel\Ai\Attributes\TopP;
use Laravel\Ai\Contracts\Agent;
use Laravel\Ai\Enums\Lab;
use Laravel\Ai\Promptable;

#[Provider(Lab::Anthropic)]
#[Model('claude-haiku-4-5-20251001')]
#[MaxSteps(10)]
#[MaxTokens(4096)]
#[Temperature(0.7)]
#[Timeout(120)]
#[TopP(0.9)]
class SalesCoach implements Agent
{
    use Promptable;
}

// 使用最便宜的模型
#[UseCheapestModel]
class SimpleSummarizer implements Agent
{
    use Promptable;
}

// 使用性能最强的模型
#[UseSmartestModel]
class ComplexReasoner implements Agent
{
    use Promptable;
}

<?php

namespace App\Ai\Agents;

use Laravel\Ai\Contracts\Agent;
use Laravel\Ai\Contracts\HasProviderOptions;
use Laravel\Ai\Enums\Lab;
use Laravel\Ai\Promptable;

class SalesCoach implements Agent, HasProviderOptions
{
    use Promptable;

    public function providerOptions(Lab|string $provider): array
    {
        return match ($provider) {
            Lab::OpenAI => [
                'reasoning' => ['effort' => 'low'],
                'frequency_penalty' => 0.5,
                'presence_penalty' => 0.3,
            ],
            Lab::Anthropic => [
                'thinking' => ['budget_tokens' => 1024],
            ],
            default => [],
        };
    }
}

use Laravel\Ai\Image;

$image = Image::of('A donut sitting on the kitchen counter')->generate();
$rawContent = (string) $image;

$image = Image::of('A donut sitting on the kitchen counter')
    ->quality('high')
    ->landscape()
    ->timeout(120)
    ->generate();

use Laravel\Ai\Files;

$image = Image::of('Update this photo to be in the style of an impressionist painting.')
    ->attachments([Files\Image::fromStorage('photo.jpg')])
    ->landscape()
    ->generate();

$path = $image->store();
$path = $image->storeAs('image.jpg');
$path = $image->storePublicly();
$path = $image->storePubliclyAs('image.jpg');

use Laravel\Ai\Responses\ImageResponse;

Image::of('A donut sitting on the kitchen counter')
    ->portrait()
    ->queue()
    ->then(function (ImageResponse $image) {
        $path = $image->store();
    });

use Laravel\Ai\Audio;

$audio = Audio::of('I love coding with Laravel.')->generate();
$rawContent = (string) $audio;

$audio = Audio::of('I love coding with Laravel.')->female()->generate();
$audio = Audio::of('I love coding with Laravel.')->voice('voice-id-or-name')->generate();
$audio = Audio::of('I love coding with Laravel.')->female()->instructions('Said like a pirate')->generate();

$path = $audio->store();
$path = $audio->storeAs('audio.mp3');
$path = $audio->storePublicly();
$path = $audio->storePubliclyAs('audio.mp3');

use Laravel\Ai\Responses\AudioResponse;

Audio::of('I love coding with Laravel.')
    ->queue()
    ->then(function (AudioResponse $audio) {
        $path = $audio->store();
    });

use Laravel\Ai\Transcription;

$transcript = Transcription::fromPath('/home/laravel/audio.mp3')->generate();
$transcript = Transcription::fromStorage('audio.mp3')->generate();
$transcript = Transcription::fromUpload($request->file('audio'))->generate();

return (string) $transcript;

$transcript = Transcription::fromStorage('audio.mp3')->diarize()->generate();

use Laravel\Ai\Responses\TranscriptionResponse;

Transcription::fromStorage('audio.mp3')
    ->queue()
    ->then(function (TranscriptionResponse $transcript) { /* ... */ });

use Illuminate\Support\Str;

// 通过 Stringable 使用
$embeddings = Str::of('Napa Valley has great wine.')->toEmbeddings();

use Laravel\Ai\Embeddings;

// 批量处理多个文本
$response = Embeddings::for(['Napa Valley has great wine.', 'Laravel is a PHP framework.'])->generate();
$response->embeddings; // [[0.123, 0.456, ...], [0.789, 0.012, ...]]

$response = Embeddings::for(['Napa Valley has great wine.'])
    ->dimensions(1536)
    ->generate(Lab::OpenAI, 'text-embedding-3-small');

$documents = Document::query()
    ->select('*')
    ->selectVectorDistance('embedding', $queryEmbedding, as: 'distance')
    ->whereVectorDistanceLessThan('embedding', $queryEmbedding, maxDistance: 0.3)
    ->orderByVectorDistance('embedding', $queryEmbedding)
    ->limit(10)
    ->get();

'caching' => [
    'embeddings' => [
        'cache' => true,
        'store' => env('CACHE_STORE', 'database'),
    ],
],

$response = Embeddings::for(['Napa Valley has great wine.'])->cache()->generate();
$response = Embeddings::for(['Napa Valley has great wine.'])->cache(seconds: 3600)->generate();

// Stringable 也一样可用
$embeddings = Str::of('Napa Valley has great wine.')->toEmbeddings(cache: true);
$embeddings = Str::of('Napa Valley has great wine.')->toEmbeddings(cache: 3600);

use Laravel\Ai\Reranking;

$response = Reranking::of([
    'Django is a Python web framework.',
    'Laravel is a PHP web application framework.',
    'React is a JavaScript library for building user interfaces.',
])->rerank('PHP frameworks');

$response->first()->document; // "Laravel is a PHP web application framework."
$response->first()->score;    // 0.95
$response->first()->index;    // 1

$response = Reranking::of($documents)->limit(5)->rerank('search query');

// 单一字段
$posts = Post::all()->rerank('body', 'Laravel tutorials');

// 多个字段（会以 JSON 发送）
$reranked = $posts->rerank(['title', 'body'], 'Laravel tutorials');

// 使用闭包自定义生成的文本
$reranked = $posts->rerank(fn ($post) => $post->title.': '.$post->body, 'Laravel tutorials');

// 带选项
$reranked = $posts->rerank(
    by: 'content',
    query: 'Laravel tutorials',
    limit: 10,
    provider: Lab::Cohere,
);

use Laravel\Ai\Files\Document;
use Laravel\Ai\Files\Image;

// 从路径
$response = Document::fromPath('/home/laravel/document.pdf')->put();
$response = Image::fromPath('/home/laravel/photo.jpg')->put();

// 从存储
$response = Document::fromStorage('document.pdf', disk: 'local')->put();
$response = Image::fromStorage('photo.jpg', disk: 'local')->put();

// 从 URL
$response = Document::fromUrl('https://example.com/document.pdf')->put();
$response = Image::fromUrl('https://example.com/photo.jpg')->put();

return $response->id;

$stored = Document::fromString('Hello, World!', 'text/plain')->put();
$stored = Document::fromUpload($request->file('document'))->put();

use Laravel\Ai\Files;

$response = (new SalesCoach)->prompt(
    'Analyze the attached sales transcript...',
    attachments: [Files\Document::fromId('file-id')]
);

// 获取
$file = Document::fromId('file-id')->get();
$file->id;
$file->mimeType();

// 删除
Document::fromId('file-id')->delete();

$response = Document::fromPath('/home/laravel/document.pdf')->put(provider: Lab::Anthropic);

use Laravel\Ai\Files\Document;

$response = Document::fromPath('/home/laravel/knowledge.txt')
    ->withProviderOptions(['purpose' => 'assistants'])
    ->put();

use Laravel\Ai\Enums\Lab;
use Laravel\Ai\Files\Document;

$response = Document::fromPath('/home/laravel/training.jsonl')
    ->withProviderOptions(fn (Lab|string $provider) => match ($provider) {
        Lab::OpenAI => ['purpose' => 'fine-tune'],
        default => [],
    })
    ->put();

use Laravel\Ai\Stores;

// 创建
$store = Stores::create('Knowledge Base');
$store = Stores::create(
    name: 'Knowledge Base',
    description: 'Documentation.',
    expiresWhenIdleFor: days(30),
);
return $store->id;

// 获取
$store = Stores::get('store_id');
$store->id;
$store->name;
$store->fileCounts;
$store->ready;

// 删除
Stores::delete('store_id');
$store->delete();

$store = Stores::get('store_id');

// 支持多种方式添加文件
$document = $store->add('file_id');
$document = $store->add(Document::fromId('file_id'));
$document = $store->add(Document::fromPath('/path/to/document.pdf'));
$document = $store->add(Document::fromStorage('manual.pdf'));
$document = $store->add($request->file('document'));

$document->id;
$document->fileId;

$store->add(
    Document::fromPath('/path/to/document.pdf'),
    metadata: [
        'author' => 'Taylor Otwell',
        'department' => 'Engineering',
        'year' => 2026,
    ]
);

$store->remove('file_id');

// 同时删除文件本身
$store->remove('file_abc123', deleteFile: true);

use App\Ai\Agents\SalesCoach;
use Laravel\Ai\Image;

// 智能体的故障切换
$response = (new SalesCoach)->prompt(
    'Analyze this sales transcript...',
    provider: [Lab::OpenAI, Lab::Anthropic],
);

// 图像生成的故障切换
$image = Image::of('A donut sitting on the kitchen counter')
    ->generate(provider: [Lab::Gemini, Lab::xAI]);

use App\Ai\Agents\SalesCoach;
use Laravel\Ai\Prompts\AgentPrompt;

// 固定响应的 fake
SalesCoach::fake();
SalesCoach::fake(['First response', 'Second response']);

// 使用闭包动态返回响应
SalesCoach::fake(function (AgentPrompt $prompt) {
    return 'Response for: '.$prompt->prompt;
});

// 断言
SalesCoach::assertPrompted('Analyze this...');
SalesCoach::assertPrompted(function (AgentPrompt $prompt) {
    return $prompt->contains('Analyze');
});
SalesCoach::assertNotPrompted('Missing prompt');
SalesCoach::assertNeverPrompted();

use Laravel\Ai\QueuedAgentPrompt;

SalesCoach::assertQueued('Analyze this...');
SalesCoach::assertQueued(function (QueuedAgentPrompt $prompt) {
    return $prompt->contains('Analyze');
});
SalesCoach::assertNotQueued('Missing prompt');
SalesCoach::assertNeverQueued();

SalesCoach::fake()->preventStrayPrompts();

SalesCoach::fake([
    ['score' => 87],
]);

use Laravel\Ai\AnonymousAgent;

AnonymousAgent::fake(['Test response']);

use Laravel\Ai\Image;
use Laravel\Ai\Prompts\ImagePrompt;

Image::fake();
Image::fake([base64_encode($firstImage), base64_encode($secondImage)]);
Image::fake(function (ImagePrompt $prompt) {
    return base64_encode('...');
});

Image::assertGenerated(function (ImagePrompt $prompt) {
    return $prompt->contains('sunset') && $prompt->isLandscape();
});
Image::assertNotGenerated('Missing prompt');
Image::assertNothingGenerated();

Image::assertQueued(fn (QueuedImagePrompt $prompt) => $prompt->contains('sunset'));
Image::assertNotQueued('Missing prompt');
Image::assertNothingQueued();

Image::fake()->preventStrayImages();

use Laravel\Ai\Audio;
use Laravel\Ai\Prompts\AudioPrompt;

Audio::fake();
Audio::fake([base64_encode($firstAudio), base64_encode($secondAudio)]);
Audio::fake(function (AudioPrompt $prompt) {
    return base64_encode('...');
});

Audio::assertGenerated(function (AudioPrompt $prompt) {
    return $prompt->contains('Hello') && $prompt->isFemale();
});
Audio::assertNotGenerated('Missing prompt');
Audio::assertNothingGenerated();

Audio::assertQueued(fn (QueuedAudioPrompt $prompt) => $prompt->contains('Hello'));
Audio::assertNotQueued('Missing prompt');
Audio::assertNothingQueued();

Audio::fake()->preventStrayAudio();

use Laravel\Ai\Transcription;
use Laravel\Ai\Prompts\TranscriptionPrompt;

Transcription::fake();
Transcription::fake(['First transcription text.', 'Second transcription text.']);
Transcription::fake(function (TranscriptionPrompt $prompt) {
    return 'Transcribed text...';
});

Transcription::assertGenerated(function (TranscriptionPrompt $prompt) {
    return $prompt->language === 'en' && $prompt->isDiarized();
});
Transcription::assertNotGenerated(fn (TranscriptionPrompt $prompt) => $prompt->language === 'fr');
Transcription::assertNothingGenerated();

Transcription::assertQueued(fn (QueuedTranscriptionPrompt $prompt) => $prompt->isDiarized());
Transcription::assertNotQueued(fn (QueuedTranscriptionPrompt $prompt) => $prompt->language === 'fr');
Transcription::assertNothingQueued();

Transcription::fake()->preventStrayTranscriptions();

use Laravel\Ai\Embeddings;
use Laravel\Ai\Prompts\EmbeddingsPrompt;

Embeddings::fake();
Embeddings::fake([[$firstEmbeddingVector], [$secondEmbeddingVector]]);
Embeddings::fake(function (EmbeddingsPrompt $prompt) {
    return array_map(
        fn () => Embeddings::fakeEmbedding($prompt->dimensions),
        $prompt->inputs
    );
});

Embeddings::assertGenerated(function (EmbeddingsPrompt $prompt) {
    return $prompt->contains('Laravel') && $prompt->dimensions === 1536;
});
Embeddings::assertNotGenerated(fn (EmbeddingsPrompt $prompt) => $prompt->contains('Other'));
Embeddings::assertNothingGenerated();

Embeddings::assertQueued(fn (QueuedEmbeddingsPrompt $prompt) => $prompt->contains('Laravel'));
Embeddings::assertNotQueued(fn (QueuedEmbeddingsPrompt $prompt) => $prompt->contains('Other'));
Embeddings::assertNothingQueued();

Embeddings::fake()->preventStrayEmbeddings();

use Laravel\Ai\Reranking;
use Laravel\Ai\Prompts\RerankingPrompt;
use Laravel\Ai\Responses\Data\RankedDocument;

Reranking::fake();
Reranking::fake([[
    new RankedDocument(index: 0, document: 'First', score: 0.95),
    new RankedDocument(index: 1, document: 'Second', score: 0.80),
]]);

Reranking::assertReranked(function (RerankingPrompt $prompt) {
    return $prompt->contains('Laravel') && $prompt->limit === 5;
});
Reranking::assertNotReranked(fn (RerankingPrompt $prompt) => $prompt->contains('Django'));
Reranking::assertNothingReranked();

use Laravel\Ai\Files;
use Laravel\Ai\Contracts\Files\StorableFile;
use Laravel\Ai\Files\Document;

Files::fake();

Document::fromString('Hello, Laravel!', mimeType: 'text/plain')->as('hello.txt')->put();

Files::assertStored(fn (StorableFile $file) =>
    (string) $file === 'Hello, Laravel!' && $file->mimeType() === 'text/plain'
);
Files::assertNotStored(fn (StorableFile $file) => (string) $file === 'Hello, World!');
Files::assertNothingStored();

Files::assertDeleted('file-id');
Files::assertNotDeleted('file-id');
Files::assertNothingDeleted();